User data store for online advertisement events

Abstract

A machine may be configured to manage user data in a user data store. For example, the machine identifies a rule associated with a campaign for serving online ads in a social networking service (SNS). The rule specifies a maximum number of user events associated with the online ads included in the campaign to occur during a time window, for a member of the SNS. The machine identifies a bucket that stores metadata pertaining to user events associated with the particular member that occurred during a time period that corresponds to the time window specified in the rule. The machine performs an analysis of the metadata pertaining to the user events associated with the particular member that occurred during the time window specified in the rule. The machine determines that, for the particular member, the rule is not violated based on the performing of the analysis of the metadata.

1 . A method comprising:
 enhancing a machine of a user data management system, the enhancing of the machine of the user data management system including incorporating one or more modules into one or more memories of the user data management system, the one or more modules configuring one or more hardware processors of the user data management system to perform operations comprising:
 identifying a rule associated with a campaign for serving online ads in a social networking service (SNS), the rule specifying a maximum number of user events of a particular type associated with the online ads included in the campaign to occur during a time window, for a member of the SNS; 
 based on the time window specified in the rule and a member identifier of a particular member of the SNS, identifying one or more buckets that store metadata pertaining to user events associated with the particular member in the one or more memories of the user data management system, the user events being tracked by a machine of a tracking system during a time period that corresponds to the time window specified in the rule; 
 performing an analysis of the metadata pertaining to the user events associated with the particular member that were tracked by the machine of a tracking system during the time window specified in the rule, the performing of the analysis including:
 accessing the one or more buckets in reverse chronological order based on time periods associated with the one or more buckets, 
 identifying a first number of user events of the particular type in a first bucket of the one or more buckets based on the metadata included in the first bucket that references the first number of user events of the particular type, 
 identifying a second number of user events of the particular type in a second bucket of the one or more buckets based on the metadata included in the second bucket that references the second number of user events of the particular type, 
 computing a total value of user events of the particular type in the first and second buckets based on the identified first number of user events and the second number of user events, and 
 comparing the total value of user events and the maximum number of user events of the particular type specified in the rule; 
 
 determining that, for the particular member, the rule is not violated based on the performing of the analysis of the metadata; and 
 based on the determining that the rule is not violated, causing a display of an ad included in the campaign in a user interface of a device associated with particular member. 
   
     
     
         2 . The method of  claim 1 , wherein the determining that, for the particular member, the rule is not violated includes determining that an ad included in the campaign should be displayed in a user interface of a device associated with the particular member. 
     
     
         3 . The method of  claim 1 , wherein the metadata includes at least one of a count of impressions served to the particular member, a count of clicks by the particular member, or a count of other events associated with the particular member. 
     
     
         4 . The method of  claim 1 , wherein the rule specifies the maximum number of user events of a particular type. 
     
     
         5 . The method of  claim 1 , wherein the metadata includes one or more values that identify one or more numbers of user events of one or more types that occurred during the time period associated with the one or more bucket. 
     
     
         6 . The method of  claim 1 , wherein the identifying of the one or more buckets includes selecting one or more buckets from a plurality of buckets associated with the particular member based on determining that the one or more buckets include metadata pertaining to one or more user events that occurred during time periods associated with the one or more buckets. 
     
     
         7 . The method of  claim 1 , wherein the identifying of the one or more buckets includes identifying one or more buckets, that store user events associated with the particular member and that are associated with one or more time periods that include the time window specified in the rule. 
     
     
         8 . The method of  claim 1 , wherein the rule specifies the maximum number of user events of a particular type, wherein the metadata includes counts of user events of one or more types, and wherein the performing of the analysis includes:
 accessing a count of the user events of the particular type in a bucket of the one or more buckets; and   comparing the count of the user events of the particular type and the maximum number of user events of the particular type specified in the rule.   
     
     
         9 . (canceled) 
     
     
         10 . The method of  claim 1 , wherein the determining, based on the time window specified in the rule, of the one or more buckets includes matching the time window and one or more time periods associated with the one or more buckets. 
     
     
         11 . The method of  claim 1 , wherein the performing of the analysis further includes:
 comparing the first number of user events of the particular type and the maximum number specified in the rule; and   determining that the maximum value exceeds the first number,   wherein the computing of the total value includes aggregating the first number of user events of the particular type and the second number of user events of the particular type based on the determining that the maximum number exceeds the first number.   
     
     
         12 . The method of  claim 1 , further comprising:
 accessing a description of a user event, the description including at least one of a member identifier of the particular member, a timestamp of the user event, a type of the user event, or a campaign identifier;   based on the accessing of the description of the user event, generating one or more update queries for one or more buckets associated with the particular member to record the description of the user event; and   based on the generating of the one or more update queries, issuing the one or more update queries to the one or more buckets associated with the particular member, the one or more update queries referencing the description of the user event.   
     
     
         13 . The method of  claim 12 , further comprising:
 identifying the type of user event associated with the user event based on the description of the user event;   based on the issuing of the one or more update queries, adding the description of the user event to a list of user event descriptions of the identified type in the one or more buckets;   increasing a list count that identifies a number of user event descriptions in the list of the identified type; and   increasing a total count that identifies a total number of user event descriptions of the identified type in the one or more buckets.   
     
     
         14 . The method of  claim 1 , further comprising:
 determining, based on one or more targeting criteria for identifying members of the SNS for presentation of online ads, that the particular member is a target member for the campaign.   
     
     
         15 . The method of  claim 1 , wherein the identifying of the rule, the identifying of the one or more buckets, and the determining that, for the particular member, the rule is not violated are performed in real time based on an indication that the particular member has logged into a web site of the SNS. 
     
     
         16 . The method of  claim 1 , wherein the one or more buckets are associated with the particular member and include a mapping from a campaign identifier of the campaign to at least one of a list of impressions associated with the campaign identifier provided to the particular member, a list of clicks associated with the campaign identifier by the particular member, or a list of other events associated with the campaign identifier and the particular member. 
     
     
         17 . A user data management system comprising:
 one or more hardware processors;   one or more modules incorporated into the data management system to enhance a machine of the user data management system, the enhancing including configuring the one or more hardware processors to perform operations comprising:   identifying a rule associated with a campaign for serving online ads in a social networking service (SNS), the rule specifying a maximum number of user events of a particular type associated with the online ads included in the campaign to occur during a time window, for a member of the SNS;   based on the time window specified in the rule and a member identifier of a particular member of the SNS, identifying one or more buckets that store metadata pertaining to user events associated with the particular member in the one or more memories of the user data management system, the user events being tracked by a machine of a tracking system during a time period that corresponds to the time window specified in the rule;   performing an analysis of the metadata pertaining to the user events associated with the particular member that were tracked by the machine of a tracking system during the time window specified in the rule, the performing of the analysis including:
 accessing the one or more buckets in reverse chronological order based on time periods associated with the one or more buckets, 
 identifying a first number of user events of the particular type in a first bucket of the one or more buckets based on the metadata included in the first bucket that references the first number of user events of the particular type, 
 identifying a second number of user events of the particular type in a second bucket of the one or more buckets based on the metadata included in the second bucket that references the second number of user events of the particular type, 
 computing a total value of user events of the particular type in the first and second buckets based on the identified first number of user events and the second number of user events, and 
 comparing the total value of user events and the maximum number of user events of the particular type specified in the rule; 
   determining that, for the particular member, the rule is not violated based on the performing of the analysis of the metadata; and   based on the determining that the rule is not violated, causing a display of an ad included in the campaign in a user interface of a device associated with particular member.   
     
     
         18 . The system of  claim 17 , wherein the operations further comprise:
 accessing a description of a user event, the description including at least one of a member identifier of the particular member, a timestamp of the user event, a type of the user event, or a campaign identifier;   based on the accessing of the description of the user event, generating one or more update queries for the one or more buckets associated with the particular member to record the description of the user event; and   based on the generating of the one or more update queries, issuing the one or more update queries to the one or more buckets associated with the particular member, the one or more update queries referencing the description of the user event.   
     
     
         19 . The system of  claim 18 , wherein the operations further comprise:
 identifying the type of user event associated with the user event based on the description of the user event;   based on the issuing of the one or more update queries, adding the description of the user event to a list of user event descriptions of the identified type in the one or more buckets;   increasing a list count that identifies a number of user event descriptions in the list of the identified type; and   increasing a total count that identifies a total number of user event descriptions of the identified type in the one or more buckets.   
     
     
         20 . A non-transitory machine-readable storage medium comprising instructions that, when incorporated into a user data management system as one or more modules implemented by one or more hardware processors of the user data management system, cause the one or more hardware processors to perform operations to enhance a machine of the user data management system, the operations comprising:
 identifying a rule associated with a campaign for serving online ads in a social networking service (SNS), the rule specifying a maximum number of user events of a particular type associated with the online ads included in the campaign to occur during a time window, for a member of the SNS;   based on the time window specified in the rule and a member identifier of a particular member of the SNS, identifying one or more buckets that store metadata pertaining to user events associated with the particular member in the one or more memories of the user data management system, the user events being tracked by a machine of a tracking system during a time period that corresponds to the time window specified in the rule;   performing an analysis of the metadata pertaining to the user events associated with the particular member that were tracked by the machine of a tracking system during the time window specified in the rule, the performing of the analysis including:
 accessing the one or more buckets in reverse chronological order based on time periods associated with the one or more buckets, 
 identifying a first number of user events of the particular type in a first bucket of the one or more buckets based on the metadata included in the first bucket that references the first number of user events of the particular type, 
 identifying a second number of user events of the particular type in a second bucket of the one or more buckets based on the metadata included in the second bucket that references the second number of user events of the particular type, 
 computing a total value of user events of the particular type in the first and second buckets based on the identified first number of user events and the second number of user events, and 
 comparing the total value of user events and the maximum number of user events of the particular type specified in the rule: 
   determining that, for the particular member, the rule is not violated based on the performing of the analysis of the metadata; and   based on the determining that the rule is not violated, causing a display of an ad included in the campaign in a user interface of a device associated with particular member.